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Kafka Streams VS Confluent

Compare Kafka Streams VS Confluent and see what are their differences

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  2. » Videos
  3. » Reviews
  4. » Alternatives

Kafka Streams logo Kafka Streams

Apache Kafka: A Distributed Streaming Platform.

Confluent logo Confluent

Confluent offers a real-time data platform built around Apache Kafka.
  • Kafka Streams Landing page
    Landing page //
    2022-11-21
  • Confluent Landing page
    Landing page //
    2023-10-22

Kafka Streams videos

+ Add

Spark Streaming Vs Kafka Streams || Which is The Best for Stream Processing?

More videos:

  • Review - Big Data Analytics in Near-Real-Time with Apache Kafka Streams - Allen Underwood
  • Review - Spring Tips: Spring Cloud Stream Kafka Streams

Confluent videos

+ Add

1. Intro | Monitoring Kafka in Confluent Control Center

More videos:

  • Review - Jason Gustafson, Confluent: Revisiting Exactly One Semantics (EOS) | Bay Area Apache Kafka® Meetup
  • Review - CLEARER SKIN AFTER 1 USE‼️| Ancient Cosmetics Update✨| CONFLUENT & RETICULATED PAPILLOMATOSIS CURE?😩

Category Popularity

0-100% (relative to Kafka Streams and Confluent)

Kafka Streams

Confluent

Stream Processing
31 31%
Stream Processing
69% 69
Big Data
26 26%
Big Data
74% 74
Analytics
41 41%
Analytics
59% 59
Data Management
0 0%
Data Management
100% 100

User comments

Share your experience with using Kafka Streams and Confluent. For example, how are they different and which one is better?
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Social recommendations and mentions

Based on our record, Kafka Streams seems to be a lot more popular than Confluent. While we know about 14 links to Kafka Streams, we've tracked only 1 mention of Confluent. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Kafka Streams mentions (14)

  • Top 10 Common Data Engineers and Scientists Pain Points in 2024
    Data scientists often prefer Python for its simplicity and powerful libraries like Pandas or SciPy. However, many real-time data processing tools are Java-based. Take the example of Kafka, Flink, or Spark streaming. While these tools have their Python API/wrapper libraries, they introduce increased latency, and data scientists need to manage dependencies for both Python and JVM environments. For example,... - Source: dev.to / about 1 month ago
  • Forward Compatible Enum Values in API with Java Jackson
    We’re not discussing the technical details behind the deduplication process. It could be Apache Flink, Apache Spark, or Kafka Streams. Anyway, it’s out of the scope of this article. - Source: dev.to / over 1 year ago
  • Kafka Internals - Learn kafka in-depth (Part-1)
    In pub-sub systems, you cannot have multiple services to consume the same data because the messages are deleted after being consumed by one consumer. Whereas in Kafka, you can have multiple services to consume. This opens the door to a lot of opportunities such as Kafka streams, Kafka connect. We’ll discuss these at the end of the series. - Source: dev.to / over 1 year ago
  • Event streaming in .Net with Kafka
    Internally, Streamiz use the .Net client for Apache Kafka released by Confluent and try to provide the same features than Kafka Streams. There is gap between these two library, but the trend is decreasing after each release. - Source: dev.to / over 1 year ago
  • Apache Pulsar vs Apache Kafka - How to choose a data streaming platform
    Both Kafka and Pulsar provide some kind of stream processing capability, but Kafka is much further along in that regard. Pulsar stream processing relies on the Pulsar Functions interface which is only suited for simple callbacks. On the other hand, Kafka Streams and ksqlDB are more complete solutions that could be considered replacements for Apache Spark or Apache Flink, state-of-the-art stream-processing... - Source: dev.to / over 1 year ago
View more

Confluent mentions (1)

  • Spring Boot Event Streaming with Kafka
    We’re going to setup a Kafka cluster using confluent.io, create a producer and consumer as well as enhance our behavior driven tests to include the new interface. We’re going to update our helm chart so that the updates are seamless to Kubernetes and we’re going to leverage our observability stack to propagate the traces in the published messages. Source: about 2 years ago

What are some alternatives?

When comparing Kafka Streams and Confluent, you can also consider the following products

Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.

Amazon Kinesis - Amazon Kinesis services make it easy to work with real-time streaming data in the AWS cloud.

Apache NiFi - An easy to use, powerful, and reliable system to process and distribute data.

Apache Airflow - Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.

Spark Streaming - Spark Streaming makes it easy to build scalable and fault-tolerant streaming applications.

KSQL - Confluent KSQL is the streaming SQL engine that enables real-time data processing against Apache Kafka®.

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